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Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

1. Which tool is best for continuous ingestion of files landing in Azure Data Lake?

A) Auto Loader
B) Azure Logic Apps
C) Databricks Jobs
D) Azure Data Factory Copy Activity

2. Hotspot Question
You have an Azure Databricks workspace that is enabled for Unity Catalog.
You need to ensure that data lineage is captured and can be reviewed for tables accessed by Databricks notebooks and jobs. The solution must minimize administrative effort.
Which compute configuration should you use to capture the data lineage and what should you use to review the data lineage? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

3. Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
You have an Azure Databricks workspace named Workspace1 that contains a lakehouse and is enabled for Unity Catalog.
You have a connection to a Microsoft SQL Server database named DB1.
You need to expose the schemas and tables of DB1 to meet the following requirements:
- The schemas and tables can be queried in Databricks.
- The schemas and tables appear alongside other Unity Catalog objects.
- The data is NOT copied into Databricks-managed storage.
Solution: You create a Databricks access connector.
Does this meet the goal?

A) No
B) Yes

4. Which Azure service is best integrated with Databricks Unity Catalog for centralized data governance?

A) Azure Key Vault
B) Azure Automation
C) Microsoft Purview
D) Azure DevTest Labs

5. What does the VACUUM command do in Delta Lake?

A) Deletes old unreferenced files
B) Optimizes query performance
C) Rewrites table schema
D) Compresses JSON files

Solutions: